Xero has delivered more than one billion machine learning recommendations to subscribers, as the company deepens efforts to automate admin offerings for small businesses.

Specifically, the accounting provider’s personalised machine learning systems delivered more than 750 million invoice and bill code recommendations, and more than 250 million bank reconciliation recommendations since the features were first launched in March last year.

Across the 800,000 invoices filed every day in Xero, the company said that small businesses have “collectively saved” in excess of 307 hours per day during the first 12 months.

“At the heart of Xero’s automation vision is to augment humans, not replace them,” Xero executive general manager of product, James Simpson, said.

“We want to reduce the burden of doing time consuming tasks to allow businesses to do more of what they love.

“The scale of what our first AI features have already achieved demonstrates the power of our innovation, and we’re excited to introduce the next wave of products to further contribute to this.”

Simpson said the milestone demonstrates the impact of Xero’s investment in automation, artificial intelligence, and machine learning.

“Since introducing the first AI-led features a year ago, automation has become a core foundation of the Xero platform to benefit the small businesses and advisors who use Xero every day,” Simpson added.

From a channel perspective, the impact of Xero’s AI milestone extends beyond small businesses to include accounting and bookkeeping partners.

“We develop products based on solving the challenges our partners and users face,” Simpson said. “Reducing the time partners have to spend on menial tasks allows them to develop the skills and capacity to build and deploy high value products and services.

“This in turn helps small businesses run more efficiently and deliver better value.”

According to Simpson, partners can now focus on delivering “higher value advisory services” to complement the provider’s push into automated solutions.